Data and Analytics Engineer

Role Overview

The Data and Analytics Engineer designs, builds, secures, and maintains CORE’s enterprise analytics data platform. This hands-on position establishes a scalable and governed data warehouse using dimensional modeling, including fact and dimension tables; automates data acquisition and integration through ETL or ELT processes; and delivers reliable, reusable data structures for reporting, advanced analytics, and future artificial intelligence capabilities.

What You Will Do

Design, build, and maintain scalable analytics data structures, develop and test ETL or ELT pipelines, manage the technical operation of the analytics platform, implement automated and repeatable controls for data quality, and develop and maintain curated datasets and governed semantic models.

Why It Might Be a Fit

The ideal candidate will have 5+ years of experience in data engineering, data warehousing, analytics engineering, business intelligence engineering, or database development, including hands-on responsibility for production data solutions, and advanced SQL skills, including database design, complex queries, stored procedures, query optimization, troubleshooting, and performance tuning in SQL Server or a comparable relational database platform.

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, software engineering, data science, analytics, or a related field, or equivalent education and directly relevant experience
• Five or more years of experience in data engineering, data warehousing, analytics engineering, business intelligence engineering, or database development, including hands-on responsibility for production data solutions
• Advanced SQL skills, including database design, complex queries, stored procedures, query optimization, troubleshooting, and performance tuning in SQL Server or a comparable relational database platform
• Demonstrated experience with dimensional data modeling, including fact and dimension tables, grain, surrogate keys, conformed dimensions, historical tracking, and star-schema design
• Experience designing and operating ETL or ELT pipelines across databases, APIs, secure files, and other enterprise sources, including incremental processing, error handling, monitoring, and recovery
• Experience with source control, structured testing, release management, operational monitoring, and separation of development, testing, and production environments
• Experience implementing data-quality controls, reconciliation, metadata, lineage, and operational documentation
• Knowledge of data security, role-based access, encryption, credential management, and privacy requirements for confidential information
• Strong analytical, problem-solving, organizational, documentation, and communication skills

Tagged as: SQL